Reporte Data Churn

Dataset statistics

Number of variables	25
Number of observations	29285
Missing cells	285132
Missing cells (%)	38.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	21.9 MiB
Average record size in memory	785.8 B

Variable types

Categorical	11
Numeric	11
Unsupported	3

Alerts

`ClaseVehiculo__c` has constant value "99999"	Constant
`TipoVehiculo__c` has constant value "99999"	Constant
`PlacaVehiculo__c` has a high cardinality: 8933 distinct values	High cardinality
`n_prod_prev` is highly correlated with `total_siniestros` and 2 other fields	High correlation
`total_siniestros` is highly correlated with `n_prod_prev` and 2 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `n_prod_prev` and 3 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `n_prod_prev` and 2 other fields	High correlation
`Activos__c` is highly correlated with `AnnualRevenue`	High correlation
`AnnualRevenue` is highly correlated with `Activos__c` and 1 other fields	High correlation
`MontoAnual__c` is highly correlated with `total_pagado_smmlv`	High correlation
`EgresosAnuales__c` is highly correlated with `AnnualRevenue`	High correlation
`total_siniestros` is highly correlated with `total_pagado_smmlv`	High correlation
`total_pagado_smmlv` is highly correlated with `total_siniestros`	High correlation
`AnnualRevenue` is highly correlated with `EgresosAnuales__c`	High correlation
`EgresosAnuales__c` is highly correlated with `AnnualRevenue`	High correlation
`total_siniestros` is highly correlated with `total_pagado_smmlv` and 1 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `total_siniestros` and 2 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `total_siniestros` and 1 other fields	High correlation
`AnnualRevenue` is highly correlated with `EgresosAnuales__c`	High correlation
`MontoAnual__c` is highly correlated with `total_pagado_smmlv`	High correlation
`EgresosAnuales__c` is highly correlated with `AnnualRevenue`	High correlation
`TipoVehiculo__c` is highly correlated with `churn` and 8 other fields	High correlation
`churn` is highly correlated with `TipoVehiculo__c` and 2 other fields	High correlation
`EstadoCivil__pc` is highly correlated with `TipoVehiculo__c` and 3 other fields	High correlation
`ClaseVehiculo__c` is highly correlated with `TipoVehiculo__c` and 8 other fields	High correlation
`CodigoTipoAsegurado__c` is highly correlated with `TipoVehiculo__c` and 4 other fields	High correlation
`ciudad_name` is highly correlated with `TipoVehiculo__c` and 2 other fields	High correlation
`tipo_ramo_name` is highly correlated with `TipoVehiculo__c` and 2 other fields	High correlation
`Genero__pc` is highly correlated with `TipoVehiculo__c` and 3 other fields	High correlation
`tipo_prod_desc` is highly correlated with `TipoVehiculo__c` and 2 other fields	High correlation
`FechaInicioVigencia__ctrim` is highly correlated with `TipoVehiculo__c` and 2 other fields	High correlation
`PuntoVenta__c` is highly correlated with `n_prod_prev` and 2 other fields	High correlation
`tipo_ramo_name` is highly correlated with `tipo_prod_desc`	High correlation
`tipo_prod_desc` is highly correlated with `tipo_ramo_name`	High correlation
`FechaInicioVigencia__ctrim` is highly correlated with `churn` and 2 other fields	High correlation
`churn` is highly correlated with `FechaInicioVigencia__ctrim` and 3 other fields	High correlation
`n_prod_prev` is highly correlated with `PuntoVenta__c` and 3 other fields	High correlation
`total_siniestros` is highly correlated with `PuntoVenta__c` and 4 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `PuntoVenta__c` and 4 other fields	High correlation
`AnnualRevenue` is highly correlated with `OtrosIngresos__c` and 1 other fields	High correlation
`OtrosIngresos__c` is highly correlated with `AnnualRevenue`	High correlation
`EgresosAnuales__c` is highly correlated with `AnnualRevenue`	High correlation
`EstadoCivil__pc` is highly correlated with `Genero__pc`	High correlation
`Genero__pc` is highly correlated with `EstadoCivil__pc`	High correlation
`MarcaVehiculo__c` has 29285 (100.0%) missing values	Missing
`MdeloVehiculo__c` has 29285 (100.0%) missing values	Missing
`PlacaVehiculo__c` has 20154 (68.8%) missing values	Missing
`n_prod_prev` has 15104 (51.6%) missing values	Missing
`total_siniestros` has 23226 (79.3%) missing values	Missing
`total_pagado_smmlv` has 23226 (79.3%) missing values	Missing
`anios_ultimo_siniestro` has 23226 (79.3%) missing values	Missing
`Activos__c` has 7741 (26.4%) missing values	Missing
`AnnualRevenue` has 7741 (26.4%) missing values	Missing
`MontoAnual__c` has 29260 (99.9%) missing values	Missing
`OtrosIngresos__c` has 9850 (33.6%) missing values	Missing
`Profesion__pc` has 29285 (100.0%) missing values	Missing
`EgresosAnuales__c` has 7741 (26.4%) missing values	Missing
`EstadoCivil__pc` has 7485 (25.6%) missing values	Missing
`Genero__pc` has 7485 (25.6%) missing values	Missing
`ciudad_name` has 7485 (25.6%) missing values	Missing
`edad` has 7553 (25.8%) missing values	Missing
`Activos__c` is highly skewed (γ1 = 99.98653783)	Skewed
`AnnualRevenue` is highly skewed (γ1 = 25.02132063)	Skewed
`OtrosIngresos__c` is highly skewed (γ1 = 82.17193257)	Skewed
`EgresosAnuales__c` is highly skewed (γ1 = 21.04856233)	Skewed
`PlacaVehiculo__c` is uniformly distributed	Uniform
`MarcaVehiculo__c` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`MdeloVehiculo__c` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Profesion__pc` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`total_pagado_smmlv` has 829 (2.8%) zeros	Zeros
`OtrosIngresos__c` has 18461 (63.0%) zeros	Zeros

Reproduction

Analysis started	2022-06-18 20:48:35.686260
Analysis finished	2022-06-18 20:49:07.495259
Duration	31.81 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

CodigoTipoAsegurado__c
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.6 MiB

1	28552
4	549
3	127
2	57

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	29285
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	28552	97.5%
4	549	1.9%
3	127	0.4%
2	57	0.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	28552	97.5%
4	549	1.9%
3	127	0.4%
2	57	0.2%

Most occurring characters

Value	Count	Frequency (%)
1	28552	97.5%
4	549	1.9%
3	127	0.4%
2	57	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	29285	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	28552	97.5%
4	549	1.9%
3	127	0.4%
2	57	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	29285	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	28552	97.5%
4	549	1.9%
3	127	0.4%
2	57	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	29285	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	28552	97.5%
4	549	1.9%
3	127	0.4%
2	57	0.2%

PuntoVenta__c
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	283
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3127.066382

Minimum	5
Maximum	20007
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	5
5-th percentile	103
Q1	902
median	2365
Q3	3303
95-th percentile	9721
Maximum	20007
Range	20002
Interquartile range (IQR)	2401

Descriptive statistics

Standard deviation	3181.762286
Coefficient of variation (CV)	1.017491123
Kurtosis	0.1990366466
Mean	3127.066382
Median Absolute Deviation (MAD)	1317
Skewness	1.263262232
Sum	91576139
Variance	10123611.25
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9721	2524	8.6%
3301	1814	6.2%
1048	1608	5.5%
103	1350	4.6%
2466	1329	4.5%
404	1241	4.2%
3202	1215	4.1%
3502	1151	3.9%
301	1064	3.6%
1503	951	3.2%
Other values (273)	15038	51.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
5	162	0.6%
8	31	0.1%
9	53	0.2%
14	124	0.4%
16	119	0.4%
23	455	1.6%
25	120	0.4%
26	89	0.3%
100	1	< 0.1%
102	9	< 0.1%

Value	Count	Frequency (%)
20007	1	< 0.1%
10111	2	< 0.1%
9977	8	< 0.1%
9974	1	< 0.1%
9973	1	< 0.1%
9972	3	< 0.1%
9971	72	0.2%
9970	4	< 0.1%
9969	39	0.1%
9967	8	< 0.1%

tipo_ramo_name
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

automoviles	26359
previhogar	2830
responsabilidad civil	96

Length

Max length	21
Median length	11
Mean length	10.93614478
Min length	10

Characters and Unicode

Total characters	320265
Distinct characters	19
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	previhogar
2nd row	previhogar
3rd row	previhogar
4th row	previhogar
5th row	previhogar

Common Values

Value	Count	Frequency (%)
automoviles	26359	90.0%
previhogar	2830	9.7%
responsabilidad civil	96	0.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
automoviles	26359	89.7%
previhogar	2830	9.6%
responsabilidad	96	0.3%
civil	96	0.3%

Most occurring characters

Value	Count	Frequency (%)
o	55644	17.4%
i	29573	9.2%
a	29381	9.2%
e	29285	9.1%
v	29285	9.1%
l	26551	8.3%
s	26551	8.3%
m	26359	8.2%
t	26359	8.2%
u	26359	8.2%
Other values (9)	14918	4.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	320169	> 99.9%
Space Separator	96	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	55644	17.4%
i	29573	9.2%
a	29381	9.2%
e	29285	9.1%
v	29285	9.1%
l	26551	8.3%
s	26551	8.3%
m	26359	8.2%
t	26359	8.2%
u	26359	8.2%
Other values (8)	14822	4.6%

Space Separator

Value	Count	Frequency (%)
	96	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	320169	> 99.9%
Common	96	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	55644	17.4%
i	29573	9.2%
a	29381	9.2%
e	29285	9.1%
v	29285	9.1%
l	26551	8.3%
s	26551	8.3%
m	26359	8.2%
t	26359	8.2%
u	26359	8.2%
Other values (8)	14822	4.6%

Common

Value	Count	Frequency (%)
	96	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	320265	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	55644	17.4%
i	29573	9.2%
a	29381	9.2%
e	29285	9.1%
v	29285	9.1%
l	26551	8.3%
s	26551	8.3%
m	26359	8.2%
t	26359	8.2%
u	26359	8.2%
Other values (9)	14918	4.7%

tipo_prod_desc
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

automoviles	26359
previhogar	2830
profesionales medicos	56
directores y administradores	38
servidores publicos	2

Length

Max length	28
Median length	11
Mean length	10.94509134
Min length	10

Characters and Unicode

Total characters	320527
Distinct characters	21
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	previhogar
2nd row	previhogar
3rd row	previhogar
4th row	previhogar
5th row	previhogar

Common Values

Value	Count	Frequency (%)
automoviles	26359	90.0%
previhogar	2830	9.7%
profesionales medicos	56	0.2%
directores y administradores	38	0.1%
servidores publicos	2	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
automoviles	26359	89.6%
previhogar	2830	9.6%
profesionales	56	0.2%
medicos	56	0.2%
directores	38	0.1%
y	38	0.1%
administradores	38	0.1%
servidores	2	< 0.1%
publicos	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
o	55796	17.4%
e	29475	9.2%
i	29419	9.2%
a	29321	9.1%
v	29191	9.1%
s	26647	8.3%
m	26453	8.3%
t	26435	8.2%
l	26417	8.2%
u	26361	8.2%
Other values (11)	15012	4.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	320393	> 99.9%
Space Separator	134	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	55796	17.4%
e	29475	9.2%
i	29419	9.2%
a	29321	9.2%
v	29191	9.1%
s	26647	8.3%
m	26453	8.3%
t	26435	8.3%
l	26417	8.2%
u	26361	8.2%
Other values (10)	14878	4.6%

Space Separator

Value	Count	Frequency (%)
	134	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	320393	> 99.9%
Common	134	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	55796	17.4%
e	29475	9.2%
i	29419	9.2%
a	29321	9.2%
v	29191	9.1%
s	26647	8.3%
m	26453	8.3%
t	26435	8.3%
l	26417	8.2%
u	26361	8.2%
Other values (10)	14878	4.6%

Common

Value	Count	Frequency (%)
	134	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	320527	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	55796	17.4%
e	29475	9.2%
i	29419	9.2%
a	29321	9.1%
v	29191	9.1%
s	26647	8.3%
m	26453	8.3%
t	26435	8.2%
l	26417	8.2%
u	26361	8.2%
Other values (11)	15012	4.7%

ClaseVehiculo__c
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

99999	29285

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	146425
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	99999
2nd row	99999
3rd row	99999
4th row	99999
5th row	99999

Common Values

Value	Count	Frequency (%)
99999	29285	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
99999	29285	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	146425	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	146425	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	146425	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	146425	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	146425	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	146425	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	146425	100.0%

MarcaVehiculo__c
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	29285
Missing (%)	100.0%
Memory size	228.9 KiB

MdeloVehiculo__c
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	29285
Missing (%)	100.0%
Memory size	228.9 KiB

PlacaVehiculo__c
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	8933
Distinct (%)	97.8%
Missing	20154
Missing (%)	68.8%
Memory size	1.2 MiB

GCZ316	3
INW085	3
JKS685	3
IIL275	2
FUR962	2
Other values (8928)	9118

Length

Max length	6
Median length	6
Mean length	5.999452415
Min length	5

Characters and Unicode

Total characters	54781
Distinct characters	36
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	8738 ?
Unique (%)	95.7%

Sample

1st row	IVW538
2nd row	TGL728
3rd row	HDQ543
4th row	HZQ669
5th row	INZ881

Common Values

Value	Count	Frequency (%)
GCZ316	3	< 0.1%
INW085	3	< 0.1%
JKS685	3	< 0.1%
IIL275	2	< 0.1%
FUR962	2	< 0.1%
FWS037	2	< 0.1%
GVO765	2	< 0.1%
SWK821	2	< 0.1%
GFR951	2	< 0.1%
GYN245	2	< 0.1%
Other values (8923)	9108	31.1%
(Missing)	20154	68.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
gcz316	3	< 0.1%
jks685	3	< 0.1%
inw085	3	< 0.1%
rlu426	2	< 0.1%
sqd730	2	< 0.1%
smw013	2	< 0.1%
szq350	2	< 0.1%
xej968	2	< 0.1%
fjs898	2	< 0.1%
tsw572	2	< 0.1%
Other values (8923)	9108	99.7%

Most occurring characters

Value	Count	Frequency (%)
0	2848	5.2%
2	2844	5.2%
7	2843	5.2%
3	2770	5.1%
1	2767	5.1%
9	2765	5.0%
4	2753	5.0%
8	2723	5.0%
5	2711	4.9%
6	2688	4.9%
Other values (26)	27069	49.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	27712	50.6%
Uppercase Letter	27069	49.4%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
S	2009	7.4%
T	1669	6.2%
W	1472	5.4%
J	1369	5.1%
G	1314	4.9%
U	1258	4.6%
R	1139	4.2%
F	1116	4.1%
M	1072	4.0%
K	1064	3.9%
Other values (16)	13587	50.2%

Decimal Number

Value	Count	Frequency (%)
0	2848	10.3%
2	2844	10.3%
7	2843	10.3%
3	2770	10.0%
1	2767	10.0%
9	2765	10.0%
4	2753	9.9%
8	2723	9.8%
5	2711	9.8%
6	2688	9.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	27712	50.6%
Latin	27069	49.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
S	2009	7.4%
T	1669	6.2%
W	1472	5.4%
J	1369	5.1%
G	1314	4.9%
U	1258	4.6%
R	1139	4.2%
F	1116	4.1%
M	1072	4.0%
K	1064	3.9%
Other values (16)	13587	50.2%

Common

Value	Count	Frequency (%)
0	2848	10.3%
2	2844	10.3%
7	2843	10.3%
3	2770	10.0%
1	2767	10.0%
9	2765	10.0%
4	2753	9.9%
8	2723	9.8%
5	2711	9.8%
6	2688	9.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54781	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2848	5.2%
2	2844	5.2%
7	2843	5.2%
3	2770	5.1%
1	2767	5.1%
9	2765	5.0%
4	2753	5.0%
8	2723	5.0%
5	2711	4.9%
6	2688	4.9%
Other values (26)	27069	49.4%

TipoVehiculo__c
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 MiB

99999	29285

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	146425
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	99999
2nd row	99999
3rd row	99999
4th row	99999
5th row	99999

Common Values

Value	Count	Frequency (%)
99999	29285	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
99999	29285	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	146425	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	146425	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	146425	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	146425	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	146425	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	146425	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	146425	100.0%

FechaInicioVigencia__ctrim
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.8 MiB

03-2020	4404
02-2021	4031
02-2018	4024
03-2018	3985
01-2018	3739
Other values (6)	9102

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	204995
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	01-2018
2nd row	01-2018
3rd row	01-2018
4th row	01-2018
5th row	01-2018

Common Values

Value	Count	Frequency (%)
03-2020	4404	15.0%
02-2021	4031	13.8%
02-2018	4024	13.7%
03-2018	3985	13.6%
01-2018	3739	12.8%
02-2019	3659	12.5%
01-2019	3598	12.3%
01-2021	1810	6.2%
03-2019	26	0.1%
02-2020	7	< 0.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
03-2020	4404	15.0%
02-2021	4031	13.8%
02-2018	4024	13.7%
03-2018	3985	13.6%
01-2018	3739	12.8%
02-2019	3659	12.5%
01-2019	3598	12.3%
01-2021	1810	6.2%
03-2019	26	0.1%
02-2020	7	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	62983	30.7%
2	51260	25.0%
1	34021	16.6%
-	29285	14.3%
8	11748	5.7%
3	8415	4.1%
9	7283	3.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	175710	85.7%
Dash Punctuation	29285	14.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	62983	35.8%
2	51260	29.2%
1	34021	19.4%
8	11748	6.7%
3	8415	4.8%
9	7283	4.1%

Dash Punctuation

Value	Count	Frequency (%)
-	29285	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	204995	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	62983	30.7%
2	51260	25.0%
1	34021	16.6%
-	29285	14.3%
8	11748	5.7%
3	8415	4.1%
9	7283	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	204995	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	62983	30.7%
2	51260	25.0%
1	34021	16.6%
-	29285	14.3%
8	11748	5.7%
3	8415	4.1%
9	7283	3.6%

churn
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.6 MiB

1	20018
0	9267

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	29285
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	20018	68.4%
0	9267	31.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	20018	68.4%
0	9267	31.6%

Most occurring characters

Value	Count	Frequency (%)
1	20018	68.4%
0	9267	31.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	29285	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	20018	68.4%
0	9267	31.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	29285	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	20018	68.4%
0	9267	31.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	29285	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	20018	68.4%
0	9267	31.6%

n_prod_prev
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	12
Distinct (%)	0.1%
Missing	15104
Missing (%)	51.6%
Infinite	0
Infinite (%)	0.0%
Mean	2.867357732

Minimum	1
Maximum	16
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	4
95-th percentile	8
Maximum	16
Range	15
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	3.232716874
Coefficient of variation (CV)	1.127420146
Kurtosis	8.098201626
Mean	2.867357732
Median Absolute Deviation (MAD)	1
Skewness	2.763255298
Sum	40662
Variance	10.45045838
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
1	6999	23.9%
2	2720	9.3%
5	2582	8.8%
3	695	2.4%
16	524	1.8%
8	278	0.9%
4	237	0.8%
14	57	0.2%
10	33	0.1%
13	28	0.1%
Other values (2)	28	0.1%
(Missing)	15104	51.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	6999	23.9%
2	2720	9.3%
3	695	2.4%
4	237	0.8%
5	2582	8.8%
6	16	0.1%
7	12	< 0.1%
8	278	0.9%
10	33	0.1%
13	28	0.1%

Value	Count	Frequency (%)
16	524	1.8%
14	57	0.2%
13	28	0.1%
10	33	0.1%
8	278	0.9%
7	12	< 0.1%
6	16	0.1%
5	2582	8.8%
4	237	0.8%
3	695	2.4%

total_siniestros
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	86
Distinct (%)	1.4%
Missing	23226
Missing (%)	79.3%
Infinite	0
Infinite (%)	0.0%
Mean	1296.323651

Minimum	1
Maximum	3469
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	114
Q3	2712
95-th percentile	3469
Maximum	3469
Range	3468
Interquartile range (IQR)	2711

Descriptive statistics

Standard deviation	1519.967527
Coefficient of variation (CV)	1.172521635
Kurtosis	-1.737231028
Mean	1296.323651
Median Absolute Deviation (MAD)	113
Skewness	0.4154775249
Sum	7854425
Variance	2310301.283
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1535	5.2%
2712	1141	3.9%
3383	907	3.1%
3469	444	1.5%
137	401	1.4%
2	383	1.3%
4	340	1.2%
3	178	0.6%
114	124	0.4%
5	72	0.2%
Other values (76)	534	1.8%
(Missing)	23226	79.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1535	5.2%
2	383	1.3%
3	178	0.6%
4	340	1.2%
5	72	0.2%
6	41	0.1%
7	53	0.2%
8	31	0.1%
9	20	0.1%
10	25	0.1%

Value	Count	Frequency (%)
3469	444	1.5%
3383	907	3.1%
2712	1141	3.9%
1403	5	< 0.1%
1303	11	< 0.1%
767	1	< 0.1%
704	1	< 0.1%
672	1	< 0.1%
594	56	0.2%
532	1	< 0.1%

total_pagado_smmlv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	1376
Distinct (%)	22.7%
Missing	23226
Missing (%)	79.3%
Infinite	0
Infinite (%)	0.0%
Mean	9170.924876

Minimum	0
Maximum	25003.07456
Zeros	829
Zeros (%)	2.8%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3.333333761
median	750.7467188
Q3	18999.25909
95-th percentile	25003.07456
Maximum	25003.07456
Range	25003.07456
Interquartile range (IQR)	18995.92576

Descriptive statistics

Standard deviation	10730.94338
Coefficient of variation (CV)	1.170104818
Kurtosis	-1.718629928
Mean	9170.924876
Median Absolute Deviation (MAD)	750.7467188
Skewness	0.4227193829
Sum	55566633.82
Variance	115153145.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
18999.25909	1141	3.9%
23810.4818	907	3.1%
0	829	2.8%
25003.07456	444	1.5%
1308.359896	401	1.4%
1.318843012	226	0.8%
750.7467188	123	0.4%
4386.12123	56	0.2%
41.55167503	20	0.1%
456.4564141	18	0.1%
Other values (1366)	1894	6.5%
(Missing)	23226	79.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	829	2.8%
0.01143934598	2	< 0.1%
0.05839231033	2	< 0.1%
0.06560781438	1	< 0.1%
0.06651725121	1	< 0.1%
0.06807237706	1	< 0.1%
0.06868550334	1	< 0.1%
0.0807227466	1	< 0.1%
0.08208084051	1	< 0.1%
0.09830500664	1	< 0.1%

Value	Count	Frequency (%)
25003.07456	444	1.5%
23810.4818	907	3.1%
18999.25909	1141	3.9%
10127.77845	5	< 0.1%
9291.89174	11	< 0.1%
8747.164104	1	< 0.1%
5779.809377	1	< 0.1%
4386.12123	56	0.2%
2952.870061	1	< 0.1%
2501.817204	1	< 0.1%

anios_ultimo_siniestro
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	853
Distinct (%)	14.1%
Missing	23226
Missing (%)	79.3%
Infinite	0
Infinite (%)	0.0%
Mean	0.4343833582

Minimum	0.002739726027
Maximum	17.61917808
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	0.002739726027
5-th percentile	0.002739726027
Q1	0.002739726027
median	0.002739726027
Q3	0.6232876712
95-th percentile	2.016438356
Maximum	17.61917808
Range	17.61643836
Interquartile range (IQR)	0.6205479452

Descriptive statistics

Standard deviation	0.8429383817
Coefficient of variation (CV)	1.94054023
Kurtosis	46.74859616
Mean	0.4343833582
Median Absolute Deviation (MAD)	0
Skewness	4.636355761
Sum	2631.928767
Variance	0.7105451154
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.002739726027	3061	10.5%
0.9890410959	227	0.8%
0.008219178082	148	0.5%
0.4356164384	23	0.1%
0.04657534247	22	0.1%
0.05753424658	20	0.1%
0.08219178082	19	0.1%
0.05479452055	18	0.1%
0.2054794521	17	0.1%
0.0904109589	17	0.1%
Other values (843)	2487	8.5%
(Missing)	23226	79.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.002739726027	3061	10.5%
0.005479452055	14	< 0.1%
0.008219178082	148	0.5%
0.01095890411	12	< 0.1%
0.01369863014	15	0.1%
0.01643835616	15	0.1%
0.01917808219	10	< 0.1%
0.02191780822	14	< 0.1%
0.02465753425	6	< 0.1%
0.02739726027	17	0.1%

Value	Count	Frequency (%)
17.61917808	1	< 0.1%
9.920547945	1	< 0.1%
9.021917808	1	< 0.1%
8.953424658	1	< 0.1%
8.698630137	1	< 0.1%
8.389041096	1	< 0.1%
8.252054795	1	< 0.1%
7.917808219	1	< 0.1%
7.512328767	1	< 0.1%
7.084931507	1	< 0.1%

Activos__c
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
SKEWED

Distinct	3955
Distinct (%)	18.4%
Missing	7741
Missing (%)	26.4%
Infinite	0
Infinite (%)	0.0%
Mean	422330779.4

Minimum	0
Maximum	1 × 10¹²
Zeros	21
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	0
5-th percentile	22000000
Q1	60000000
median	120000000
Q3	257407500
95-th percentile	990926950
Maximum	1 × 10¹²
Range	1 × 10¹²
Interquartile range (IQR)	197407500

Descriptive statistics

Standard deviation	9756606654
Coefficient of variation (CV)	23.10181292
Kurtosis	10229.14145
Mean	422330779.4
Median Absolute Deviation (MAD)	80000000
Skewness	99.98653783
Sum	9.09869431 × 10¹²
Variance	9.51913734 × 10¹⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100000000	1079	3.7%
80000000	816	2.8%
150000000	766	2.6%
200000000	760	2.6%
50000000	655	2.2%
120000000	590	2.0%
60000000	566	1.9%
40000000	478	1.6%
30000000	449	1.5%
90000000	447	1.5%
Other values (3945)	14938	51.0%
(Missing)	7741	26.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	21	0.1%
1	72	0.2%
2	3	< 0.1%
20	2	< 0.1%
40	3	< 0.1%
50	1	< 0.1%
80	1	< 0.1%
100	3	< 0.1%
104	1	< 0.1%
350	1	< 0.1%

Value	Count	Frequency (%)
1 × 10¹²	2	< 0.1%
1 × 10¹¹	2	< 0.1%
5.835 × 10¹⁰	1	< 0.1%
5.43154931 × 10¹⁰	1	< 0.1%
4.479 × 10¹⁰	1	< 0.1%
4.0078653 × 10¹⁰	3	< 0.1%
3.1092794 × 10¹⁰	3	< 0.1%
2.8125029 × 10¹⁰	2	< 0.1%
2.43 × 10¹⁰	1	< 0.1%
2.0615603 × 10¹⁰	1	< 0.1%

AnnualRevenue
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	3904
Distinct (%)	18.1%
Missing	7741
Missing (%)	26.4%
Infinite	0
Infinite (%)	0.0%
Mean	215724725.8

Minimum	0
Maximum	8.63 × 10¹⁰
Zeros	8
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	0
5-th percentile	8500000
Q1	25200000
median	43375000
Q3	80000000
95-th percentile	479991450
Maximum	8.63 × 10¹⁰
Range	8.63 × 10¹⁰
Interquartile range (IQR)	54800000

Descriptive statistics

Standard deviation	1593181656
Coefficient of variation (CV)	7.385252895
Kurtosis	891.9396781
Mean	215724725.8
Median Absolute Deviation (MAD)	21625000
Skewness	25.02132063
Sum	4.647573494 × 10¹²
Variance	2.538227789 × 10¹⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
36000000	1115	3.8%
60000000	874	3.0%
24000000	839	2.9%
30000000	796	2.7%
48000000	674	2.3%
18000000	464	1.6%
12000000	402	1.4%
50000000	401	1.4%
40000000	395	1.3%
42000000	326	1.1%
Other values (3894)	15258	52.1%
(Missing)	7741	26.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	8	< 0.1%
1	27	0.1%
20	2	< 0.1%
52230	1	< 0.1%
250000	1	< 0.1%
328000	1	< 0.1%
350000	1	< 0.1%
500000	3	< 0.1%
600000	1	< 0.1%
700000	3	< 0.1%

Value	Count	Frequency (%)
8.63 × 10¹⁰	1	< 0.1%
6.6728 × 10¹⁰	1	< 0.1%
6 × 10¹⁰	2	< 0.1%
4.1610143 × 10¹⁰	2	< 0.1%
3.6110425 × 10¹⁰	5	< 0.1%
3.5084 × 10¹⁰	2	< 0.1%
2.6097952 × 10¹⁰	2	< 0.1%
2.576590619 × 10¹⁰	2	< 0.1%
2.469016564 × 10¹⁰	3	< 0.1%
2.3626255 × 10¹⁰	2	< 0.1%

MontoAnual__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	12
Distinct (%)	48.0%
Missing	29260
Missing (%)	99.9%
Infinite	0
Infinite (%)	0.0%
Mean	2005177.64

Minimum	0
Maximum	50000000
Zeros	10
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	100
Q3	10000
95-th percentile	24321
Maximum	50000000
Range	50000000
Interquartile range (IQR)	10000

Descriptive statistics

Standard deviation	9998924.797
Coefficient of variation (CV)	4.98655311
Kurtosis	24.99996075
Mean	2005177.64
Median Absolute Deviation (MAD)	100
Skewness	4.99999434
Sum	50129441
Variance	9.997849709 × 10¹³
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
0	10	< 0.1%
3000	3	< 0.1%
21605	2	< 0.1%
18000	2	< 0.1%
10000	1	< 0.1%
5525	1	< 0.1%
600	1	< 0.1%
50000000	1	< 0.1%
25000	1	< 0.1%
5	1	< 0.1%
Other values (2)	2	< 0.1%
(Missing)	29260	99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	10	< 0.1%
1	1	< 0.1%
5	1	< 0.1%
100	1	< 0.1%
600	1	< 0.1%
3000	3	< 0.1%
5525	1	< 0.1%
10000	1	< 0.1%
18000	2	< 0.1%
21605	2	< 0.1%

Value	Count	Frequency (%)
50000000	1	< 0.1%
25000	1	< 0.1%
21605	2	< 0.1%
18000	2	< 0.1%
10000	1	< 0.1%
5525	1	< 0.1%
3000	3	< 0.1%
600	1	< 0.1%
100	1	< 0.1%
5	1	< 0.1%

OtrosIngresos__c
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
SKEWED
ZEROS

Distinct	292
Distinct (%)	1.5%
Missing	9850
Missing (%)	33.6%
Infinite	0
Infinite (%)	0.0%
Mean	2736204.184

Minimum	0
Maximum	8400000000
Zeros	18461
Zeros (%)	63.0%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	24000
Maximum	8400000000
Range	8400000000
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	75798999.89
Coefficient of variation (CV)	27.70224544
Kurtosis	8236.986482
Mean	2736204.184
Median Absolute Deviation (MAD)	0
Skewness	82.17193257
Sum	5.317812832 × 10¹⁰
Variance	5.745488384 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	18461	63.0%
12000000	53	0.2%
10000000	38	0.1%
6000000	33	0.1%
24000000	31	0.1%
30000000	31	0.1%
5000000	26	0.1%
18000000	22	0.1%
20000000	19	0.1%
15000000	17	0.1%
Other values (282)	704	2.4%
(Missing)	9850	33.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	18461	63.0%
9583	1	< 0.1%
24000	2	< 0.1%
178000	2	< 0.1%
183000	1	< 0.1%
200000	6	< 0.1%
201105	2	< 0.1%
228000	1	< 0.1%
239000	1	< 0.1%
240000	2	< 0.1%

Value	Count	Frequency (%)
8400000000	1	< 0.1%
3439000000	2	< 0.1%
1664801000	4	< 0.1%
936054000	1	< 0.1%
928737000	1	< 0.1%
862423500	2	< 0.1%
590960000	2	< 0.1%
436838000	1	< 0.1%
398188968	1	< 0.1%
268346000	3	< 0.1%

Profesion__pc
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	29285
Missing (%)	100.0%
Memory size	228.9 KiB

EgresosAnuales__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	2996
Distinct (%)	13.9%
Missing	7741
Missing (%)	26.4%
Infinite	0
Infinite (%)	0.0%
Mean	138388559.1

Minimum	0
Maximum	3.6967344 × 10¹⁰
Zeros	15
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	0
5-th percentile	3000000
Q1	12000000
median	24000000
Q3	48000000
95-th percentile	350000000
Maximum	3.6967344 × 10¹⁰
Range	3.6967344 × 10¹⁰
Interquartile range (IQR)	36000000

Descriptive statistics

Standard deviation	976454775.4
Coefficient of variation (CV)	7.055892349
Kurtosis	570.954123
Mean	138388559.1
Median Absolute Deviation (MAD)	14000000
Skewness	21.04856233
Sum	2.981443117 × 10¹²
Variance	9.534639283 × 10¹⁷
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
12000000	1137	3.9%
30000000	948	3.2%
24000000	913	3.1%
18000000	857	2.9%
20000000	838	2.9%
36000000	514	1.8%
15000000	494	1.7%
10000000	493	1.7%
40000000	488	1.7%
25000000	427	1.5%
Other values (2986)	14435	49.3%
(Missing)	7741	26.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	15	0.1%
1	148	0.5%
10	8	< 0.1%
18	1	< 0.1%
100	1	< 0.1%
204	1	< 0.1%
20000	1	< 0.1%
50000	2	< 0.1%
70000	1	< 0.1%
72000	3	< 0.1%

Value	Count	Frequency (%)
3.6967344 × 10¹⁰	2	< 0.1%
3.0868341 × 10¹⁰	5	< 0.1%
2.2582482 × 10¹⁰	2	< 0.1%
2.166849912 × 10¹⁰	4	< 0.1%
2.1322738 × 10¹⁰	2	< 0.1%
1.9746108 × 10¹⁰	2	< 0.1%
1.923885007 × 10¹⁰	3	< 0.1%
1.8035021 × 10¹⁰	1	< 0.1%
1.629516502 × 10¹⁰	1	< 0.1%
1.4868 × 10¹⁰	2	< 0.1%

EstadoCivil__pc
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	8
Distinct (%)	< 0.1%
Missing	7485
Missing (%)	25.6%
Memory size	1.5 MiB

SOLTERO	10290
CASADO	9471
OTRO	1546
UNIDO	294
VIUDO	74
Other values (3)	125

Length

Max length	10
Median length	8
Mean length	6.325825688
Min length	3

Characters and Unicode

Total characters	137903
Distinct characters	15
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	SOLTERO
2nd row	CASADO
3rd row	SOLTERO
4th row	CASADO
5th row	SOLTERO

Common Values

Value	Count	Frequency (%)
SOLTERO	10290	35.1%
CASADO	9471	32.3%
OTRO	1546	5.3%
UNIDO	294	1.0%
VIUDO	74	0.3%
SEPARADO	68	0.2%
DIVORCIADO	44	0.2%
N A	13	< 0.1%
(Missing)	7485	25.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
soltero	10290	47.2%
casado	9471	43.4%
otro	1546	7.1%
unido	294	1.3%
viudo	74	0.3%
separado	68	0.3%
divorciado	44	0.2%
n	13	0.1%
a	13	0.1%

Most occurring characters

Value	Count	Frequency (%)
O	33667	24.4%
S	19829	14.4%
A	19135	13.9%
R	11948	8.7%
T	11836	8.6%
E	10358	7.5%
L	10290	7.5%
D	9995	7.2%
C	9515	6.9%
I	456	0.3%
Other values (5)	874	0.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	137890	> 99.9%
Space Separator	13	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
O	33667	24.4%
S	19829	14.4%
A	19135	13.9%
R	11948	8.7%
T	11836	8.6%
E	10358	7.5%
L	10290	7.5%
D	9995	7.2%
C	9515	6.9%
I	456	0.3%
Other values (4)	861	0.6%

Space Separator

Value	Count	Frequency (%)
	13	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	137890	> 99.9%
Common	13	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
O	33667	24.4%
S	19829	14.4%
A	19135	13.9%
R	11948	8.7%
T	11836	8.6%
E	10358	7.5%
L	10290	7.5%
D	9995	7.2%
C	9515	6.9%
I	456	0.3%
Other values (4)	861	0.6%

Common

Value	Count	Frequency (%)
	13	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	137903	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
O	33667	24.4%
S	19829	14.4%
A	19135	13.9%
R	11948	8.7%
T	11836	8.6%
E	10358	7.5%
L	10290	7.5%
D	9995	7.2%
C	9515	6.9%
I	456	0.3%
Other values (5)	874	0.6%

Genero__pc
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	< 0.1%
Missing	7485
Missing (%)	25.6%
Memory size	1.6 MiB

MASCULINO	16001
FEMENINO	5792
N A	7

Length

Max length	9
Median length	9
Mean length	8.732385321
Min length	3

Characters and Unicode

Total characters	190366
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	MASCULINO
2nd row	FEMENINO
3rd row	MASCULINO
4th row	MASCULINO
5th row	FEMENINO

Common Values

Value	Count	Frequency (%)
MASCULINO	16001	54.6%
FEMENINO	5792	19.8%
N A	7	< 0.1%
(Missing)	7485	25.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
masculino	16001	73.4%
femenino	5792	26.6%
n	7	< 0.1%
a	7	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
N	27592	14.5%
M	21793	11.4%
I	21793	11.4%
O	21793	11.4%
A	16008	8.4%
S	16001	8.4%
C	16001	8.4%
U	16001	8.4%
L	16001	8.4%
E	11584	6.1%
Other values (2)	5799	3.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	190359	> 99.9%
Space Separator	7	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	27592	14.5%
M	21793	11.4%
I	21793	11.4%
O	21793	11.4%
A	16008	8.4%
S	16001	8.4%
C	16001	8.4%
U	16001	8.4%
L	16001	8.4%
E	11584	6.1%

Space Separator

Value	Count	Frequency (%)
	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	190359	> 99.9%
Common	7	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	27592	14.5%
M	21793	11.4%
I	21793	11.4%
O	21793	11.4%
A	16008	8.4%
S	16001	8.4%
C	16001	8.4%
U	16001	8.4%
L	16001	8.4%
E	11584	6.1%

Common

Value	Count	Frequency (%)
	7	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	190366	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	27592	14.5%
M	21793	11.4%
I	21793	11.4%
O	21793	11.4%
A	16008	8.4%
S	16001	8.4%
C	16001	8.4%
U	16001	8.4%
L	16001	8.4%
E	11584	6.1%
Other values (2)	5799	3.0%

ciudad_name
Categorical

HIGH CORRELATION
MISSING

Distinct	22
Distinct (%)	0.1%
Missing	7485
Missing (%)	25.6%
Memory size	1.6 MiB

otras	17023
BOGOTÁ D.C.	1549
MEDELLIN	674
CALI	651
CARTAGENA	189
Other values (17)	1714

Length

Max length	13
Median length	5
Mean length	5.77766055
Min length	4

Characters and Unicode

Total characters	125953
Distinct characters	31
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	otras
2nd row	otras
3rd row	otras
4th row	PASTO
5th row	otras

Common Values

Value	Count	Frequency (%)
otras	17023	58.1%
BOGOTÁ D.C.	1549	5.3%
MEDELLIN	674	2.3%
CALI	651	2.2%
CARTAGENA	189	0.6%
VILLAVICENCIO	182	0.6%
ARMENIA	176	0.6%
BUCARAMANGA	174	0.6%
PASTO	167	0.6%
MANIZALES	160	0.5%
Other values (12)	855	2.9%
(Missing)	7485	25.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
otras	17023	72.5%
bogotá	1549	6.6%
d.c	1549	6.6%
medellin	674	2.9%
cali	651	2.8%
cartagena	189	0.8%
villavicencio	182	0.8%
armenia	176	0.7%
bucaramanga	174	0.7%
pasto	167	0.7%
Other values (17)	1152	4.9%

Most occurring characters

Value	Count	Frequency (%)
o	17023	13.5%
r	17023	13.5%
a	17023	13.5%
s	17023	13.5%
t	17023	13.5%
A	4078	3.2%
O	3823	3.0%
C	3240	2.6%
.	3098	2.5%
L	2975	2.4%
Other values (21)	23624	18.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	85115	67.6%
Uppercase Letter	36054	28.6%
Other Punctuation	3098	2.5%
Space Separator	1686	1.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	4078	11.3%
O	3823	10.6%
C	3240	9.0%
L	2975	8.3%
I	2682	7.4%
E	2480	6.9%
D	2353	6.5%
T	2070	5.7%
G	2019	5.6%
N	1918	5.3%
Other values (14)	8416	23.3%

Lowercase Letter

Value	Count	Frequency (%)
o	17023	20.0%
r	17023	20.0%
a	17023	20.0%
s	17023	20.0%
t	17023	20.0%

Other Punctuation

Value	Count	Frequency (%)
.	3098	100.0%

Space Separator

Value	Count	Frequency (%)
	1686	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	121169	96.2%
Common	4784	3.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	17023	14.0%
r	17023	14.0%
a	17023	14.0%
s	17023	14.0%
t	17023	14.0%
A	4078	3.4%
O	3823	3.2%
C	3240	2.7%
L	2975	2.5%
I	2682	2.2%
Other values (19)	19256	15.9%

Common

Value	Count	Frequency (%)
.	3098	64.8%
	1686	35.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	124160	98.6%
None	1793	1.4%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	17023	13.7%
r	17023	13.7%
a	17023	13.7%
s	17023	13.7%
t	17023	13.7%
A	4078	3.3%
O	3823	3.1%
C	3240	2.6%
.	3098	2.5%
L	2975	2.4%
Other values (18)	21831	17.6%

None

Value	Count	Frequency (%)
Á	1628	90.8%
Ú	112	6.2%
É	53	3.0%

edad
Real number (ℝ_≥0)

MISSING

Distinct	10412
Distinct (%)	47.9%
Missing	7553
Missing (%)	25.8%
Infinite	0
Infinite (%)	0.0%
Mean	50.3867382

Minimum	1.42739726
Maximum	122.5424658
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	228.9 KiB

Quantile statistics

Minimum	1.42739726
5-th percentile	29.1509589
Q1	39.74794521
median	49.54520548
Q3	60.25068493
95-th percentile	73.98082192
Maximum	122.5424658
Range	121.1150685
Interquartile range (IQR)	20.50273973

Descriptive statistics

Standard deviation	14.19263628
Coefficient of variation (CV)	0.2816740435
Kurtosis	0.3553377722
Mean	50.3867382
Median Absolute Deviation (MAD)	10.24931507
Skewness	0.3639585464
Sum	1095004.595
Variance	201.4309247
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
46.72054795	80	0.3%
47.54794521	77	0.3%
42.49041096	41	0.1%
122.5424658	27	0.1%
43.71780822	22	0.1%
36.53972603	20	0.1%
47.72054795	16	0.1%
71.55616438	14	< 0.1%
53.49589041	13	< 0.1%
41.61369863	13	< 0.1%
Other values (10402)	21409	73.1%
(Missing)	7553	25.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.42739726	1	< 0.1%
3.405479452	1	< 0.1%
3.438356164	1	< 0.1%
4.263013699	1	< 0.1%
4.287671233	1	< 0.1%
4.367123288	1	< 0.1%
4.380821918	2	< 0.1%
4.42739726	1	< 0.1%
4.460273973	2	< 0.1%
4.794520548	1	< 0.1%

Value	Count	Frequency (%)
122.5424658	27	0.1%
104.9863014	2	< 0.1%
103.1041096	3	< 0.1%
100.0493151	1	< 0.1%
98.52876712	2	< 0.1%
96.39452055	2	< 0.1%
96.3260274	2	< 0.1%
96.1369863	1	< 0.1%
95.54794521	2	< 0.1%
95.46575342	2	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	CodigoTipoAsegurado__c	PuntoVenta__c	tipo_ramo_name	tipo_prod_desc	ClaseVehiculo__c	MarcaVehiculo__c	MdeloVehiculo__c	PlacaVehiculo__c	TipoVehiculo__c	FechaInicioVigencia__ctrim	churn	n_prod_prev	total_siniestros	total_pagado_smmlv	anios_ultimo_siniestro	Activos__c	AnnualRevenue	MontoAnual__c	OtrosIngresos__c	Profesion__pc	EgresosAnuales__c	EstadoCivil__pc	Genero__pc	ciudad_name	edad
0	1	404	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	0	NaN	NaN	NaN	NaN	1.320000e+08	7.000000e+05	NaN	NaN	NaN	1.000000e+00	SOLTERO	MASCULINO	otras	49.257534
1	1	103	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	0	NaN	NaN	NaN	NaN	3.000000e+07	2.090000e+07	NaN	NaN	NaN	1.820000e+07	CASADO	FEMENINO	otras	83.991781
2	1	5	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	1	NaN	NaN	NaN	NaN	3.434361e+09	7.238820e+08	NaN	0.0	NaN	5.662310e+08	SOLTERO	MASCULINO	otras	37.389041
3	1	1402	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	1	2.0	NaN	NaN	NaN	4.260000e+08	1.123034e+08	NaN	100000000.0	NaN	9.600000e+07	CASADO	MASCULINO	PASTO	50.161644
4	1	7002	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	1	NaN	NaN	NaN	NaN	6.000000e+07	2.900000e+07	NaN	NaN	NaN	2.900000e+07	SOLTERO	FEMENINO	otras	37.106849
5	1	7007	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	1	1.0	NaN	NaN	NaN	2.068315e+08	7.445627e+07	NaN	0.0	NaN	6.645600e+07	OTRO	MASCULINO	BOGOTÁ D.C.	38.383562
6	1	404	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	0	NaN	NaN	NaN	NaN	6.000000e+08	4.900000e+07	NaN	NaN	NaN	3.500000e+07	OTRO	FEMENINO	otras	78.463014
7	1	404	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	1	NaN	NaN	NaN	NaN	1.700000e+08	3.600000e+07	NaN	NaN	NaN	2.400000e+07	OTRO	FEMENINO	CALI	72.504110
8	1	404	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	0	NaN	NaN	NaN	NaN	1.360000e+08	1.450000e+07	NaN	9000000.0	NaN	2.350000e+07	CASADO	MASCULINO	CALI	82.301370
9	1	404	previhogar	previhogar	99999	NaN	NaN	NaN	99999	01-2018	0	NaN	NaN	NaN	NaN	2.361596e+09	2.776884e+09	NaN	NaN	NaN	1.853277e+09	OTRO	MASCULINO	CALI	63.627397

Last rows

	CodigoTipoAsegurado__c	PuntoVenta__c	tipo_ramo_name	tipo_prod_desc	ClaseVehiculo__c	MarcaVehiculo__c	MdeloVehiculo__c	PlacaVehiculo__c	TipoVehiculo__c	FechaInicioVigencia__ctrim	churn	n_prod_prev	total_siniestros	total_pagado_smmlv	anios_ultimo_siniestro	Activos__c	AnnualRevenue	MontoAnual__c	OtrosIngresos__c	Profesion__pc	EgresosAnuales__c	EstadoCivil__pc	Genero__pc	ciudad_name	edad
29275	1	3301	responsabilidad civil	profesionales medicos	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	NaN	NaN	NaN	324578000.0	83160000.0	NaN	0.0	NaN	1.0	OTRO	MASCULINO	otras	61.082192
29276	1	3301	responsabilidad civil	directores y administradores	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
29277	1	1048	responsabilidad civil	directores y administradores	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
29278	1	1048	responsabilidad civil	directores y administradores	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	2.0	1.415121	0.397260	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
29279	1	3301	responsabilidad civil	profesionales medicos	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	NaN	NaN	NaN	18000000.0	60000000.0	NaN	0.0	NaN	58000000.0	CASADO	MASCULINO	BOGOTÁ D.C.	NaN
29280	1	3301	responsabilidad civil	directores y administradores	99999	NaN	NaN	NaN	99999	02-2021	1	14.0	704.0	5779.809377	0.063014	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
29281	3	3202	responsabilidad civil	profesionales medicos	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
29282	1	8001	responsabilidad civil	profesionales medicos	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	NaN	NaN	NaN	500000000.0	90000000.0	NaN	0.0	NaN	65000000.0	SOLTERO	MASCULINO	BOGOTÁ D.C.	122.542466
29283	1	8001	responsabilidad civil	directores y administradores	99999	NaN	NaN	NaN	99999	02-2021	0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
29284	1	8001	responsabilidad civil	directores y administradores	99999	NaN	NaN	NaN	99999	02-2021	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts